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This introduction to Natural Language Processing, or NLP for short, describes a central problems of artificial intelligence. NLP is focused on the interactions between human language and computers, and it sits at the intersection of computer science, artificial intelligence, and computational linguistics.

NLP is characterized as a hard problem in computer science. Human language is rarely precise, or plainly spoken. To understand human language is to understand not only the words, but the concepts and how they’re linked together to create meaning. Despite language being one of the easiest things for humans to learn, the ambiguity of language is what makes natural language processing a difficult problem for computers to master.

Natural Language Processing Algorithms

NLP algorithms are typically based on machine learning algorithms. Instead of hand-coding large sets of rules, NLP can rely on machine learning to automatically learn these rules by analyzing a set of examples (i.e. a large corpus, like a book, down to a collection of sentences), and making a statical inference. In general, the more data analyzed, the more accurate the model will be.

These libraries provide the algorithmic building blocks of NLP in real-world applications. Algorithmia provides a free API endpoint for many of these algorithms, without ever having to setup or provision servers and infrastructure.

A Few NLP Examples:

Use Summarizer to automatically summarize a block of text, exacting topic sentences, and ignoring the rest.

Speech and Language Processing, 2nd Edition 2nd Edition
“An explosion of Web-based language techniques, merging of distinct fields, availability of phone-based dialogue systems, and much more make this an exciting time in speech and language processing. The first of its kind to thoroughly cover language technology – at all levels and with all modern technologies – this text takes an empirical approach to the subject, based on applying statistical and other machine-learning algorithms to large corporations. The authors cover areas that traditionally are taught in different courses, to describe a unified vision of speech and language processing.”

Introduction to Information Retrieval “As recently as the 1990s, studies showed that most people preferred getting information from other people rather than from information retrieval systems. However, during the last decade, relentless optimization of information retrieval effectiveness has driven web search engines to new quality levels where most people are satisfied most of the time, and web search has become a standard and often preferred source of information finding. For example, the 2004 Pew Internet Survey (Fallows, 2004) found that 92% of Internet users say the Internet is a good place to go for getting everyday information.” To the surprise of many, the field of information retrieval has moved from being a primarily academic discipline to being the basis underlying most people’s preferred means of information access.”

Stanford Machine Learning on Coursera
“Machine learning is the science of getting computers to act without being explicitly programmed. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.”

Udemy’s Introduction to Natural Language Processing
“This course introduces Natural Language Processing through the use of python and the Natural Language Tool Kit. Through a practical approach, you’ll get hands on experience working with and analyzing text. As a student of this course, you’ll get updates for free, which include lecture revisions, new code examples, and new data projects.”

Certificate in Natural Language Technology
“When you talk to your mobile device or car navigation system – or it talks to you – you’re experiencing the fruits of developments in natural language processing. This field, which focuses on the creation of software that can analyze and understand human languages, has grown rapidly in recent years and now has many technological applications. In this three-course certificate program, we’ll explore the foundations of computational linguistics, the academic discipline that underlies NLP.”